SRY-box transcription factor 10 is a highly specific biomarker of basal-like breast cancer.

AIMS: Basal-like breast cancer is an aggressive molecular subtype associated with younger age and early relapse. Most cases lack expression of oestrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor 2, limiting targeted therapeutic options. Basal-like breast cancer is defined by the expression of genes in the outer/basally located epithelial layer of mammary glands, including those encoding cytokeratin (CK) 5 and CK14, and epidermal growth factor receptor (EGFR). SRY-box transcription factor 10 (SOX10), for which there is a readily available immunohistochemical stain, is expressed in a subset of breast cancers, particularly triple-negative carcinomas. In this study, we sought to: (i) assess the association between SOX10 expression and intrinsic molecular subtypes as defined by Prediction Analysis of Microarray 50 (PAM50) gene expression; and (ii) compare the performance of SOX10 with that of other surrogate markers of the basal-like subtype, including CK5, EGFR, nestin, and inositol polyphosphate 4-phosphatase type II (INPP4B). METHODS AND RESULTS: SOX10 immunostaining was performed on tissue microarrays constructed from a contemporary series enriched for ER-negative and weakly ER-positive cancers that had also undergone PAM50 gene profiling. A total of 211 cases were informative for both SOX10 immunohistochemistry and PAM50 subtype, including 103 basal-like cancers. Staining for SOX10 was positive in 73 of 103 basal-like cancers and in only two of 108 cancers of other subtypes (P < 0.001), resulting in a sensitivity of 70.9% and a specificity of 98.1%. SOX10 was more specific than the other tested basal markers, and the results were independent of ER status. CONCLUSIONS: SOX10 is a moderately sensitive, but highly specific, immunohistochemical biomarker for the basal-like intrinsic subtype of breast cancer, which, unlike other commonly used immunohistochemical biomarkers, is independent of hormone receptor status.

Differential expression and prognostic relevance of autophagy-related markers ATG4B, GABARAP, and LC3B in breast cancer.

PURPOSE: Previous studies indicate that breast cancer molecular subtypes differ with respect to their dependency on autophagy, but our knowledge of the differential expression and prognostic significance of autophagy-related biomarkers in breast cancer is limited. METHODS: Immunohistochemistry (IHC) was performed on tissue microarrays from a large population of 3992 breast cancer patients divided into training and validation cohorts. Consensus staining scores were used to evaluate the expression levels of autophagy proteins LC3B, ATG4B, and GABARAP and determine the associations with clinicopathological variables and molecular biomarkers. Survival analyses were performed using the Kaplan-Meier function and Cox proportional hazards regression models. RESULTS: We found subtype-specific expression differences for ATG4B, with its expression lowest in basal-like breast cancer and highest in Luminal A, but there were no significant associations with patient prognosis. LC3B and GABARAP levels were highest in basal-like breast cancers, and high levels were associated with worse outcomes across all subtypes (DSS; GABARAP: HR 1.43, LC3B puncta: HR 1.43). High ATG4B levels were associated with ER, PR, and BCL2 positivity, while high LC3B and GABARAP levels were associated with ER, PR, and BCL2 negativity, as well as EGFR, HER2, HER3, CA-IX, PD-L1 positivity, and high Ki67 index (p < 0.05 for all associations). Exploratory multi-marker analysis indicated that the combination of ATG4B and GABARAP with LC3B could be useful for further stratifying patient outcomes. CONCLUSIONS: ATG4B levels varied across breast cancer subtypes but did not show prognostic significance. High LC3B expression and high GABARAP expression were both associated with poor prognosis and with clinicopathological characteristics of aggressive disease phenotypes in all breast cancer subtypes.

Basal biomarkers nestin and INPP4B predict gemcitabine benefit in metastatic breast cancer: Samples from the phase III SBG0102 clinical trial.

In a formal prospective-retrospective analysis of the phase III SBG0102 clinical trial randomizing metastatic breast cancer patients to gemcitabine-docetaxel or to single agent docetaxel, patients with basal-like tumors by PAM50 gene expression had significantly better overall survival in the gemcitabine arm. By immunohistochemistry (IHC), triple negative status was not predictive, but more specific biomarkers have since become available defining basal-like by nestin positivity or loss of inositol-polyphosphate-4-phosphate (INPP4B). Here, we evaluate their capacity to identify which patients benefit from gemcitabine in the metastatic setting. Nestin and INPP4B staining and interpretation followed published methods. A prespecified statistical plan evaluated the primary hypothesis that patients with basal-like breast cancer, defined as "nestin+ or INPP4B-", would have superior overall survival on gemcitabine-docetaxel when compared to docetaxel. Interaction tests, Kaplan-Meier curves and forest plots were used to assess prognostic and predictive capacities of biomarkers relative to treatment. Among 239 cases evaluable for our study, 36 (15%) had been classified as basal-like by PAM50. "Nestin+ or INPP4B-" was observed in 41 (17%) of the total cases and was significantly associated with PAM50 basal-like subtype. Within an estimated median follow-up of 13 years, patients assigned as IHC basal "nestin+ or INPP4B-" had significantly better overall survival on gemcitabine-docetaxel versus docetaxel monotherapy (HR = 0.31, 95%CI: 0.16-0.60), whereas no differences were observed for other patients (HR = 0.99), p-interaction < 0.01. In the metastatic setting, women with IHC basal breast cancers defined as "nestin+ or INPP4B-" have superior overall survival when randomized to gemcitabine-containing chemotherapy compared to docetaxel alone. These findings need to be validated using larger prospective-retrospective phase III clinical trials series.

Nestin expression in breast cancer: association with prognosis and subtype on 3641 cases with long-term follow-up.

BACKGROUND: Basal-like breast cancers, originally recognized by gene expression profiling, can be clinically identified using immunohistochemical (IHC) definitions that require estrogen receptor (ER) negativity. However, some basal cases are ER positive and are mistakenly considered to be luminal by standard IHC approaches, leading to suboptimal treatment choices. Nestin, an intermediate filament expressed in many stem cells, is a recently identified positive marker of basal-like phenotype independent of ER status. In this study, we evaluated its clinical associations and prognostic capacity in a large breast cancer cohort. METHODS: A tissue microarray series of clinically annotated invasive breast cancers with 12.6-year median follow-up was assessed for nestin expression by IHC. Kaplan-Meier and Cox regression models were used to evaluate the prognostic significance of nestin status, for the primary endpoint of breast cancer-specific survival (BCSS). RESULTS: Among 3641 cases interpretable for nestin by IHC, positive staining was found in 371 cases (10%) and was significantly associated with poor prognostic factors including other markers of basal-like differentiation. Patients with nestin-positive tumors had a significantly lower 10 year BCSS (HR 1.97, 95% CI 1.62-2.40; P < 0.001). Importantly, within the large group of 2323 ER+ cases, nestin positivity identified a subgroup of 120 patients (5%) with a significantly inferior 10-year BCSS (HR 1.50, 95% CI 1.10-2.13; P = 0.02). CONCLUSIONS: Nestin IHC positivity is associated with the poor clinical outcomes and reduced survival rates that characterize the gene expression basal-like subtype. This easily applicable tool identifies ER+ poor prognosis basal phenotype patients that are currently being missed by "Triple negative" or "Core basal" IHC definitions.

Tumor Copy Number Alteration Burden as a Predictor for Resistance to Immune Checkpoint Blockade across Different Cancer Types.

Immune checkpoint blockade (ICB) benefits only a subset of advanced cancer patients, and predictive biomarkers for immunotherapy response are needed. Recently, copy number alteration (CNA) burden has been proposed to predict ICB resistance. We assessed this finding using the publicly accessible data for 1661 ICB-treated patients whose tumors were profiled by MSK-IMPACT, an approved targeted assay in clinical care. We tested the hypothesis that the continuous increase in CNA burden is associated with poor overall survival following ICB. In addition, we hypothesized that the combinatorial biomarkers of tumor mutational burden (TMB) and CNA burden would better stratify patients for immune status and ICB response. Of the 1661 cases, 79% (n = 1307) were treated with anti PD-1/PD-L1 and the remaining 21% (n = 354) with anti CTLA-4 or the combination of both. In a multivariate analysis, increase in CNA burden was associated with poor overall survival [HR = 1.52, 95% CI (1.01-2.30), p = 0.04]. The combination of biomarkers TMB and CNA burden stratified patients into four clinically distinct subsets among which "LowTMB/HighCNA" showed the worst survival (p < 0.0001). The four patient subsets had unique CNA profiles and enriched pathways, which could predict transcriptional and phenotypic effects related to immune signaling and CD8+ T-cell abundance in the tumor microenvironment. CNA burden was associated with poor overall survival in patients receiving ICB and could improve patient stratification when incorporated with TMB. These findings may guide patient selection for immunotherapy or alternative strategies.

Extracellular vesicle-based liquid biopsy biomarkers and their application in precision immuno-oncology.

While the field of precision oncology is rapidly expanding and more targeted options are revolutionizing cancer treatment paradigms, therapeutic resistance particularly to immunotherapy remains a pressing challenge. This can be largely attributed to the dynamic tumor-stroma interactions that continuously alter the microenvironment. While to date most advancements have been made through examining the clinical utility of tissue-based biomarkers, their invasive nature and lack of a holistic representation of the evolving disease in a real-time manner could result in suboptimal treatment decisions. Thus, using minimally-invasive approaches to identify biomarkers that predict and monitor treatment response as well as alert to the emergence of recurrences is of a critical need. Currently, research efforts are shifting towards developing liquid biopsy-based biomarkers obtained from patients over the course of disease. Liquid biopsy represents a unique opportunity to monitor intercellular communication within the tumor microenvironment which could occur through the exchange of extracellular vesicles (EVs). EVs are lipid bilayer membrane nanoscale vesicles which transfer a plethora of biomolecules that mediate intercellular crosstalk, shape the tumor microenvironment, and modify drug response. The capture of EVs using innovative approaches, such as microfluidics, magnetic beads, and aptamers, allow their analysis via high throughput multi-omics techniques and facilitate their use for biomarker discovery. Artificial intelligence, using machine and deep learning algorithms, is advancing multi-omics analyses to uncover candidate biomarkers and predictive signatures that are key for translation into clinical trials. With the increasing recognition of the role of EVs in mediating immune evasion and as a valuable biomarker source, these real-time snapshots of cellular communication are promising to become an important tool in the field of precision oncology and spur the recognition of strategies to block resistance to immunotherapy. In this review, we discuss the emerging role of EVs in biomarker research describing current advances in their isolation and analysis techniques as well as their function as mediators in the tumor microenvironment. We also highlight recent lung cancer and melanoma studies that point towards their application as predictive biomarkers for immunotherapy and their potential clinical use in precision immuno-oncology.

Triple-Negative PAM50 Non-Basal Breast Cancer Subtype Predicts Benefit from Extended Adjuvant Capecitabine.

PURPOSE: Predictive biomarkers for capecitabine benefit in triple-negative breast cancer (TNBC) have been recently proposed using samples from phase III clinical trials, including non-basal phenotype and biomarkers related to angiogenesis, stroma, and capecitabine activation genes. We aimed to validate these findings on the larger phase III GEICAM/CIBOMA clinical trial. EXPERIMENTAL DESIGN: Tumor tissues from patients with TNBC randomized to standard (neo)adjuvant chemotherapy followed by capecitabine versus observation were analyzed using a 164-gene NanoString custom nCounter codeset measuring mRNA expression. A prespecified statistical plan sought to verify the predictive capacity of PAM50 non-basal molecular subtype and tested the hypotheses that breast tumors with increased expression of (meta)genes for cytotoxic cells, mast cells, endothelial cells, PDL2, and 38 individual genes benefit from adjuvant capecitabine for distant recurrence-free survival (DRFS; primary endpoint) and overall survival. RESULTS: Of the 876 women enrolled in the GEICAM/CIBOMA trial, 658 (75%) were evaluable for analysis (337 with capecitabine and 321 without). Of these cases, 553 (84%) were profiled as PAM50 basal-like whereas 105 (16%) were PAM50 non-basal. Non-basal subtype was the most significant predictor for capecitabine benefit [HRcapecitabine, 0.19; 95% confidence interval (CI), 0.07-0.54; P < 0.001] when compared with PAM50 basal-like (HRcapecitabine, 0.9; 95% CI, 0.63-1.28; P = 0.55; Pinteraction<0.001, adjusted P value = 0.01). Analysis of biological processes related to PAM50 non-basal subtype revealed its enrichment for mast cells, extracellular matrix, angiogenesis, and features of mesenchymal stem-like TNBC subtype. CONCLUSIONS: In this prespecified correlative analysis of the GEICAM/CIBOMA trial, PAM50 non-basal status identified patients with early-stage TNBC most likely to benefit from capecitabine.

Heterogeneity of triple negative breast cancer: Current advances in subtyping and treatment implications.

As the field of translational 'omics has progressed, refined classifiers at both genomic and proteomic levels have emerged to decipher the heterogeneity of breast cancer in a clinically-applicable way. The integration of 'omics knowledge at the DNA, RNA and protein levels is further expanding biologic understanding of breast cancer and opportunities for customized treatment, a particularly pressing need in clinically triple negative tumors. For this group of aggressive breast cancers, work from multiple groups has now validated at least four major biologically and clinically distinct omics-based subtypes. While to date most clinical trial designs have considered triple negative breast cancers as a single group, with an expanding arsenal of targeted therapies applicable to distinct biological pathways, survival benefits may be best realized by designing and analyzing clinical trials in the context of major molecular subtypes. While RNA-based classifiers are the most developed, proteomic classifiers proposed for triple negative breast cancer based on new technologies have the potential to more directly identify the most clinically-relevant biomarkers and therapeutic targets. Phospho-proteomic data further identify targetable signalling pathways in a unique subtype-specific manner. Single cell profiling of the tumor microenvironment represents a promising way to allow a better characterization of the heterogeneity of triple negative breast cancer which could be integrated in a spatially resolved context to build an ecosystem-based patient classification. Multi-omic data further allows in silico analysis of genetic and pharmacologic screens to map therapeutic vulnerabilities in a subtype-specific context. This review describes current knowledge about molecular subtyping of triple negative breast cancer, recent advances in omics-based genomics and proteomics diagnostics addressing the diversity of this disease, key advances made through single cell analysis approaches, and developments in treatments including targeted therapeutics being tested in major clinical trials.

Neither Tumor-Infiltrating Lymphocytes nor Cytotoxic T Cells Predict Enhanced Benefit from Chemotherapy in the DBCG77B Phase III Clinical Trial.

Recent studies have shown that immune infiltrates in the tumor microenvironment play a role in response to therapy, with some suggesting that patients with immunogenic tumors may receive increased benefit from chemotherapies. We evaluated this hypothesis in early breast cancer by testing the interaction between immune biomarkers and chemotherapy using materials from DBCG77B, a phase III clinical trial where high-risk premenopausal women were randomized to receive chemotherapy or no chemotherapy. Tissue microarrays were evaluated for tumor-infiltrating lymphocytes (TILs) assessed morphologically on hematoxylin and eosin-stained slides, and by immunohistochemistry for CD8, FOXP3, LAG-3, PD-1 and PD-L1. Following REMARK reporting guidelines, data analyses were performed according to a prespecified statistical plan, using 10-year invasive disease-free survival as the endpoint. Differences in survival probabilities between biomarker groups were evaluated by Kaplan-Meier and Cox proportional hazard ratio analyses and prediction for treatment benefit by an interaction test. Our results showed that stromal TILs were associated with an improved prognosis (HR = 0.93; p-value = 0.03), consistent with previous studies. However, none of the immune biomarkers predicted benefit from chemotherapy in the full study set nor within major breast cancer subtypes. Our study indicates that primary tumors with higher immune infiltration do not derive extra benefit from cyclophosphamide-based cytotoxic chemotherapy.

Proteomic analysis of archival breast cancer clinical specimens identifies biological subtypes with distinct survival outcomes.

Despite advances in genomic classification of breast cancer, current clinical tests and treatment decisions are commonly based on protein level information. Formalin-fixed paraffin-embedded (FFPE) tissue specimens with extended clinical outcomes are widely available. Here, we perform comprehensive proteomic profiling of 300 FFPE breast cancer surgical specimens, 75 of each PAM50 subtype, from patients diagnosed in 2008-2013 (n = 178) and 1986-1992 (n = 122) with linked clinical outcomes. These two cohorts are analyzed separately, and we quantify 4214 proteins across all 300 samples. Within the aggressive PAM50-classified basal-like cases, proteomic profiling reveals two groups with one having characteristic immune hot expression features and highly favorable survival. Her2-Enriched cases separate into heterogeneous groups differing by extracellular matrix, lipid metabolism, and immune-response features. Within 88 triple-negative breast cancers, four proteomic clusters display features of basal-immune hot, basal-immune cold, mesenchymal, and luminal with disparate survival outcomes. Our proteomic analysis characterizes the heterogeneity of breast cancer in a clinically-applicable manner, identifies potential biomarkers and therapeutic targets, and provides a resource for clinical breast cancer classification.

Proteomics-derived basal biomarker DNA-PKcs is associated with intrinsic subtype and long-term clinical outcomes in breast cancer.

Precise biomarkers are needed to guide better diagnostics and therapeutics for basal-like breast cancer, for which DNA-dependent protein kinase catalytic subunit (DNA-PKcs) has been recently reported by the Clinical Proteomic Tumor Analysis Consortium as the most specific biomarker. We evaluated DNA-PKcs expression in clinically-annotated breast cancer tissue microarrays and correlated results with immune biomarkers (training set: n = 300; validation set: n = 2401). Following a pre-specified study design per REMARK criteria, we found that high expression of DNA-PKcs was significantly associated with stromal and CD8 + tumor infiltrating lymphocytes. Within the basal-like subtype, tumors with low DNA-PKcs and high tumor-infiltrating lymphocytes displayed the most favourable survival. DNA-PKcs expression by immunohistochemistry identified estrogen receptor-positive cases with a basal-like gene expression subtype. Non-silent mutations in PRKDC were significantly associated with poor outcomes. Integrating DNA-PKcs expression with validated immune biomarkers could guide patient selection for DNA-PKcs targeting strategies, DNA-damaging agents, and their combination with an immune-checkpoint blockade.

Predictive Significance of an Optimized Panel for Basal-like Breast Cancer: Results from the Canadian Cancer Trials Group MA.5 and MA.12 Phase III Clinical Trials.

PURPOSE: Accurate IHC biomarkers incorporating nestin positivity or inositol polyphosphate-4-phosphate (INPP4B) loss have recently been optimized to identify the basal-like intrinsic breast cancer subtype regardless of estrogen, progesterone, or Her2 status. We examined the predictive capacity of these basal biomarkers in the CCTG MA.5 chemotherapy and MA.12 endocrine therapy trials. EXPERIMENTAL DESIGN: Formalin-fixed paraffin embedded blocks of primary tumors from patients randomized in the two trials were used to build tissue microarrays. IHC staining for nestin and INPP4B followed published methods and REMARK criteria. A prespecified statistical plan tested the hypothesis that patients with basal breast cancer (nestin+ or INPP4B-) would not benefit from anthracycline substitution in MA.5 or from tamoxifen in MA.12. RESULTS: Nestin positivity or INPP4B loss was observed in 110/453 (24%) interpretable samples from MA.5 and 47/366 (13%) from MA.12, and was associated with high grade, younger age, estrogen receptor negativity, triple-negative, core basal, and PAM50 basal-like subtypes. In the MA.5 trial, patients assigned as basal experienced lower benefit from anthracycline versus nonanthracycline adjuvant chemotherapy [HR, 1.49; 95% confidence interval (CI), 0.72-3.10] when compared with non-basal (nestin- and INPP4B+) cases where there was a higher benefit from anthracyclines (HR, 0.75; 95% CI, 0.54-1.04; P interaction = 0.01). In the MA.12 trial, patients assigned as basal did not demonstrate a benefit from adjuvant tamoxifen versus placebo (HR, 0.48; 95% CI, 0.12-1.86; P = 0.29), whereas nonbasal cases displayed significant benefit (HR, 0.66; 95% CI, 0.45-0.98; P = 0.04), although the interaction test was not significant. CONCLUSIONS: The nestin/INPP4B IHC panel identifies women with basal breast cancers who benefit from nonanthracycline chemotherapy but not endocrine adjuvant treatments.

The immune microenvironment and relation to outcome in patients with advanced breast cancer treated with docetaxel with or without gemcitabine.

Preclinical studies suggest that some effects of conventional chemotherapy, and in particular, gemcitabine, are mediated through enhanced antitumor immune responses. The objective of this study was to use material from a randomized clinical trial to evaluate whether patients with preexisting immune infiltrates responded better to treatment with gemcitabine + docetaxel (GD) compared to docetaxel alone. Formalin fixed, paraffin-embedded breast cancer tissues from SBG0102 phase 3 trial patients randomly assigned to treatment with GD or docetaxel were used. Immunohistochemical staining for CD8, FOXP3, LAG3, PD-1, PD-L1 and CD163 was performed. Tumor infiltrating lymphocytes (TILs) and tumor associated macrophages were evaluated. Prespecified statistical analyses were performed in a formal prospective-retrospective design. Time to progression was primary endpoint and overall survival secondary endpoint. Correlations between biomarker status and endpoints were evaluated using the Kaplan-Meier method and Cox proportional hazards models. Biomarker data was obtained for 237 patients. There was no difference in treatment effect according to biomarker status for the whole cohort. In planned subgroup analysis by PAM50 subtype, in non-luminal (basal-like and HER2E) breast cancers FOXP3 was a significant predictor of treatment effect with GD compared to docetaxel, with a HR of 0.22 (0.09-0.52) for tumors with low FOXP3 compared to HR 0.92 (0.47-1.80) for high FOXP3 TILs (Pinteraction = 0.01). Immune biomarkers were not predictive of added benefit of gemcitabine in a cohort of mixed breast cancer subtypes. However, in non-luminal breast cancers, patients with low FOXP3+ TILs may have significant benefit from added gemcitabine.

Predictive Biomarkers for Adjuvant Capecitabine Benefit in Early-Stage Triple-Negative Breast Cancer in the FinXX Clinical Trial.

PURPOSE: Recent studies have demonstrated a benefit of adjuvant capecitabine in early breast cancer, particularly in patients with triple-negative breast cancer (TNBC). However, TNBC is heterogeneous and more precise predictive biomarkers are needed. EXPERIMENTAL DESIGN: Tumor tissues collected from TNBC patients in the FinXX trial, randomized to adjuvant anthracycline-taxane-based chemotherapy with or without capecitabine, were analyzed using a 770-gene panel targeting multiple biological mechanisms and additional 30-custom genes related to capecitabine metabolism. Hypothesis-generating exploratory analyses were performed to assess biomarker expression in relation to treatment effect using the Cox regression model and interaction tests adjusted for multiplicity. RESULTS: One hundred eleven TNBC samples were evaluable (57 without capecitabine and 54 with capecitabine). The median follow-up was 10.2 years. Multivariate analysis showed significant improvement in recurrence-free survival (RFS) favoring capecitabine in four biologically important genes and metagenes, including cytotoxic cells [hazard ratio (HR) = 0.38; 95% confidence intervals (CI), 0.16-0.86, P-interaction = 0.01], endothelial (HR = 0.67; 95% CI, 0.20-2.22, P-interaction = 0.02), mast cells (HR = 0.78; 95% CI, 0.49-1.27, P-interaction = 0.04), and PDL2 (HR = 0.31; 95% CI, 0.12-0.81, P-interaction = 0.03). Furthermore, we identified 38 single genes that were significantly associated with capecitabine benefit, and these were dominated by immune response pathway and enzymes involved in activating capecitabine to fluorouracil, including TYMP. However, these results were not significant when adjusted for multiple testing. CONCLUSIONS: Genes and metagenes related to antitumor immunity, immune response, and capecitabine activation could identify TNBC patients who are more likely to benefit from adjuvant capecitabine. Given the reduced power to observe significant findings when correcting for multiplicity, our findings provide the basis for future hypothesis-testing validation studies on larger clinical trials.

Phospho-Ser784-VCP Is Required for DNA Damage Response and Is Associated with Poor Prognosis of Chemotherapy-Treated Breast Cancer.

Spatiotemporal protein reorganization at DNA damage sites induced by genotoxic chemotherapies is crucial for DNA damage response (DDR), which influences treatment response by directing cancer cell fate. This process is orchestrated by valosin-containing protein (VCP), an AAA+ ATPase that extracts polyubiquinated chromatin proteins and facilitates their turnover. However, because of the essential and pleiotropic effects of VCP in global proteostasis, it remains challenging practically to understand and target its DDR-specific functions. We describe a DNA-damage-induced phosphorylation event (Ser784), which selectively enhances chromatin-associated protein degradation mediated by VCP and is required for DNA repair, signaling, and cell survival. These functional effects of Ser784 phosphorylation on DDR correlate with a decrease in VCP association with chromatin, cofactors NPL4/UFD1, and polyubiquitinated substrates. Clinically, high phospho-Ser784-VCP levels are significantly associated with poor outcome among chemotherapy-treated breast cancer patients. Thus, Ser784 phosphorylation is a DDR-specific enhancer of VCP function and a potential predictive biomarker for chemotherapy treatments.

Association between low admission Norton scale scores and postoperative complications after elective THA in elderly patients.

The Norton scoring system is used by nurses to evaluate pressure ulcer risk. The authors have previously shown that low admission Norton scale scores (ANSS) are associated with postoperative complications other than pressure ulcers following hip fracture and spine fracture surgery in elderly patients. The purpose of this retrospective, cross-sectional study study was to determine whether low ANSS are associated with postoperative complications other than pressure ulcers following elective total hip arthroplasty (THA) in elderly patients. The medical charts of consecutive elderly (older than 65 years) patients admitted between February 2008 and November 2010 were studied for acute renal failure, cardiovascular events, confusion, pneumonia, pressure ulcers, urinary infection, urinary retention, venous thromboembolism, wound infection, and other complications. The final cohort included 166 patients (108 [65.1%] women; aged 75.2±6.4 years). Overall, 24 (14.5%) patients had low (16 or less) ANSS. Patients with low ANSS had significantly more postoperative complications other than pressure ulcers compared with patients with high ANSS (0.5±0.7 vs 0.2±0.4, respectively; P=.018). Binary regression analysis showed that low ANSS were independently associated with all postoperative complications other than pressure ulcers (P=.039). In addition to predicting pressure ulcer risk, the Norton scoring system may be used for predicting other postoperative complications in elderly patients following elective THA.